ACUTE RENAL FAILURE - CHANGING TRENDS.
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ABSTRACT:
SUBMITTER: Narula AS
PROVIDER: S-EPMC5529769 | biostudies-other | 1994 Apr
REPOSITORIES: biostudies-other
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Project description:Metastatic calcification, a known complication of prolonged end-stage renal disease, is herein described for the first time in a 10-month-old boy with acute renal failure, manifesting as a painful and swollen arm. Imaging revealed diffuse calcification and technetium-99 methylene diphosphonate (99Tc-MDP) uptake around the humerus and axilla. Calcium and vitamin D restriction, followed by intravenous administration of sodium thiosulfate caused a full symptomatic, radio- and scintigraphic improvement.
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Project description:Traumatic and nontraumatic rhabdomyolysis can lead to acute renal failure (ARF), and acute alcohol intoxication can lead to multiple abnormalities of the renal tubules. We examined the effect of acute alcohol intoxication in a rat model of rhabdomyolysis and ARF. Intravenous injections of 5 g/kg ethanol were given to rats over 3 h, followed by glycerol-induced rhabdomyolysis. Biochemical parameters, including blood urea nitrogen (BUN), creatinine (Cre), glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT), and creatine phosphokinase (CPK), were measured before and after induction of rhabdomyolysis. Renal tissue injury score, renal tubular cell expression of E-cadherin, nuclear factor-κB (NF-κB), and inducible nitric oxide synthase (iNOS) were determined. Relative to rats in the vehicle group, rats in the glycerol-induced rhabdomyolysis group had significantly increased serum levels of BUN, Cre, GOT, GPT, and CPK, elevated renal tissue injury scores, increased expression of NF-κB and iNOS, and decreased expression of E-cadherin. Ethanol exacerbated all of these pathological responses. Our results suggest that acute alcohol intoxication exacerbates rhabdomyolysis-induced ARF through its pro-oxidant and inflammatory effects.
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Project description:We describe a 59-year-old patient who developed acute renal failure because of rhabdomyolysis after extensive red fire ant bites. This case illustrates a serious systemic reaction that may occur from fire ant bites. Consistent with the clinical presentation in rhabdomyolysis associated with non-traumatic causes, hyperkalemia, hypophosphatemia, hypocalcemia, and high anion gap acidosis were not observed in this patient. While local allergic reactions to fire ant bites are described in the literature, serious systemic complications with rhabdomyolysis and renal failure have not been previously reported. It is our effort to alert the medical community of the possibility of such a complication that can occur in the victims of fire ant bites.
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Project description:A prospective study of 82 patients with acute renal failure was carried out over the last 2 years. Mean age of the patients was 35.6 years (8-82 years). Male to female ratio was 3.5:1. The etiological factors were septicaemia in 18 patients (21.95%), aminoglycoside toxicity in 16 patients (19.51%), open heart surgery in 8 patients (9.76%), volume depletion and blood loss in 12 patients (14.63%), glomerulonephritis in 4 patients (4.88%), renal allograft dysfunction in 4 patients (4.88%), and miscellaneous causes in 20 patients (24.39%). Non-oliguric renal failure was observed in 39.02 per cent cases. Dialysis support was required in 65.8 per cent of the cases; with average 5.6 (4 to 11) dialysis sessions. Four patients of acute renal failure following open heart surgery were given continuous arterio-venous haemofiltration. Overall mortality was 32.5 per cent, septicaemia accounting for 60 per cent of the deaths.
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Project description:BackgroundAcute renal failure (ARF) is the most common major complication following cardiac surgery for acute aortic syndrome (AAS) and worsens the postoperative prognosis. Our aim was to establish a machine learning prediction model for ARF occurrence in AAS patients.MethodsWe included AAS patient data from nine medical centers (n = 1,637) and analyzed the incidence of ARF and the risk factors for postoperative ARF. We used data from six medical centers to compare the performance of four machine learning models and performed internal validation to identify AAS patients who developed postoperative ARF. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to compare the performance of the predictive models. We compared the performance of the optimal machine learning prediction model with that of traditional prediction models. Data from three medical centers were used for external validation.ResultsThe eXtreme Gradient Boosting (XGBoost) algorithm performed best in the internal validation process (AUC = 0.82), which was better than both the logistic regression (LR) prediction model (AUC = 0.77, p < 0.001) and the traditional scoring systems. Upon external validation, the XGBoost prediction model (AUC =0.81) also performed better than both the LR prediction model (AUC = 0.75, p = 0.03) and the traditional scoring systems. We created an online application based on the XGBoost prediction model.ConclusionsWe have developed a machine learning model that has better predictive performance than traditional LR prediction models as well as other existing risk scoring systems for postoperative ARF. This model can be utilized to provide early warnings when high-risk patients are found, enabling clinicians to take prompt measures.
| S-EPMC8801502 | biostudies-literature
Project description:AimsThe importance of true worsening renal failure (WRF), which is associated with a poor prognosis, had been suggested in patients with acute heart failure (AHF). The aim of the present study was to establish the biomarker strategy for the prediction of true WRF in AHF.Methods and resultsTwo hundred eighty-one patients with AHF were analysed. Their biomarkers were measured within 30 min of admission. Patients were assigned to the non-WRF (n = 168), pseudo-WRF (n = 56), or true-WRF (n = 57) groups using the criteria of both acute kidney injury on admission and increasing serum creatinine value during the first 7 days. A Kaplan-Meier curve showed that the survival and heart failure event rate of the true-WRF group within 1000 days was significantly lower than that of the non-WRF and pseudo-WRF groups (P ≤ 0.001). The multivariate Cox regression model also indicated that true WRF was an independent predictor of 1000 day mortality and heart failure events [hazard ratio: 4.315, 95% confidence interval (CI): 2.466-7.550, P ≤ 0.001, and hazard ratio: 2.834, 95% CI: 1.893-4.243, P ≤ 0.001, respectively]. The serum heart-type fatty acid-binding protein (s-HFABP) levels were significantly higher in the true-WRF group than in the non-WRF and pseudo-WRF groups (P ≤ 0.001). The multivariate logistic regression model indicated that the predictive biomarker for the true-WRF group was the s-HFABP level (odds ratio: 5.472, 95% CI: 2.729-10.972, P ≤ 0.001). The sensitivity and specificity for indicating the presence of true WRF were 73.7% and 76.8% (area under the curve = 0.831) for s-HFABP in whole patients, respectively, and 94.7% and 72.7% (area under the curve = 0.904) in non-chronic kidney disease (CKD) patients, respectively.ConclusionsCardiac biomarkers, especially the s-HFABP, might predict the development of true WRF in AHF patients. Furthermore, the predictive value was higher in AHF patients without CKD than in those with CKD.
| S-EPMC6437438 | biostudies-literature
Project description:IntroductionRenal scintigraphy (RS) is occasionally performed to assess the risk of persistent renal failure (PRF) in patients with acute kidney disease (AKD). However, its diagnostic performance has never been assessed.MethodsWe identified all patients with AKD for whom RS was performed in our institution between 2010 and 2017. PRF was defined as persistently low (< 33% of baseline) estimated glomerular filtration rates (eGFR), 1 year after RS. Nuclear medicine specialists reviewed RS data and rated, for each patient, the likelihood of PRF ("PRF score"). We evaluated the performance to predict PRF (area under the ROC curve (AUC)) of RS-derived parameters such as renal accumulation index, accumulation slope, and new parameters derived from serial kidney activity counts. We tested the ability of those parameters to improve a clinical model including hypertension, diabetes, AKI severity and baseline eGFR. Finally, we conducted sensitivity analyses using alternate PRF definitions.ResultsAmong 97 patients included, 57 (59%) fulfilled the criteria for PRF. The PRF score was able to predict PRF with an AUC of 0.63. Similarly, the accumulation index and accumulation slope respective AUCs were 0.64 and 0.63. None of these parameters were able to improve the performance of the clinical model. Among new parameters, the 3rd/2nd minute activity ratio and 3rd/2nd minute activity slope had fair diagnostic performance (AUC 0.72 and 0.74, respectively) and improved the performance of the clinical model. Results were confirmed in sensitivity analyses.ConclusionConventional renal scintigraphy can identify patients at high risk of PRF with a high specificity but a low sensitivity. New parameters, with comparable diagnostic abilities can be obtained within three minutes of injection.
| S-EPMC10226915 | biostudies-literature
Project description:BackgroundAlthough acute kidney injury (AKI) often accompanies acute liver failure (ALF), its impact on long-term outcome is unknown.ObjectiveThis study examines the incidence, severity and outcomes of AKI in patients with ALF.MethodsA total of 134 ALF patients treated at Hannover Medical School between 1995 and 2013 were retrospectively analyzed.ResultsFifty-four ALF patients (40.3%) demonstrated AKI, as defined by the acute kidney injury network (AKIN) classification, on intensive care unit (ICU) admission, and 85 patients (63.4%) developed AKI prior to ALF recovery, emergency liver transplantation (ELT) or death. AKI severity was closely associated with other end-organ damage (p < 0.001). Follow-up creatinine levels in survivors were increased compared to baseline levels (76 versus 64 µmol/l, p = 0.003). One-hundred-and-three (76.9%) patients reached the combined endpoint of ELT or death, and 42 (31.3%) patients died within 28 days. AKIN stage 3 at ICU admission was the strongest independent predictor of 28-day overall mortality (hazard ratio 3.48, 95% confidence interval 1.75-6.93, p < 0.001) and ELT or death (hazard ratio 2.52, 95% confidence interval 1.60-3.96, p < 0.001).ConclusionsAKI is a frequent complication in ALF that correlates with remote organ damage and long-term creatinine levels and independently predicts outcome.
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Project description:OBJECTIVE:To determine whether the inferior vena cava (IVC) measurement by bedside ultrasound (US-IVC) predicts improvement in renal function in patients with acute kidney injury (AKI). DESIGN:Prospective observational study. SETTING:Medical intensive care unit. PATIENTS:33 patients with AKI were included. INTERVENTION:US-IVC was done on admission. The patients' management was done by the primary teams, who were unaware of the US-IVC findings. Two groups of patients were identified. Group 1 included patients who were managed in concordance with their US-IVC (potential volume responders who had a positive fluid balance at 48 h after admission and potential volume nonresponders who had an even or negative fluid balance at 48 hours after admission). Group 2 included patients in whom the fluid management was discordant with their US-IVC. MEASUREMENTS AND MAIN RESULTS:At 48 hours, Group 1 patients had a greater improvement in creatinine [85% versus 31%, p = 0.0002], creatinine clearance (78 ± 93% versus 8 ± 64%, p = 0.002), and urine output (0.86 ± 0.54 versus 0.45 ± 0.36 ml/Kg/h, p = 0.03). CONCLUSION:In critically ill patients with AKI, concurrence of fluid therapy with IVC predicted fluid management, as assessed by bedside ultrasound, was associated with improved renal function at 48 hours. This trial is registered with ClinicalTrials.gov registration number: NCT02064244.
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